A benign DoS occurs when a service is running on insufficient resources, when there has been an unforeseen popularity or traffic spike, or when something about the supporting system fails, such as drive loss, network link drop, or a corrupted configuration. This type of DoS occurs through no direct or intentional malign action on the part of an adversary. It is due to innocent events, unexpected conditions, or mistakes on the part of the owners/operators. For more on DoS, see Chapter 17.

If you have an interest in HPC systems and want to keep up with the latest developments and which system has the highest performance, visit top500.org.

A concept related to HPC is that of the real-time OS (RTOS). Often HPCs implement RTOS compute capability or otherwise attempt to achieve real-time processing and operations.

A real-time operating system (RTOS) is designed to process or handle data as it arrives on the system with minimal latency or delay. An RTOS is usually stored on read-only memory (ROM) and is designed to operate in a hard real-time or soft real-time condition. A hard real-time solution is for mission-critical operations where delay must be eliminated or minimized for safety, such as autonomous cars. A soft real-time solution is used when some level of modest delay is acceptable under typical or normal conditions, as it is for most consumer electronics, such as the delay between a digitizing pen and a graphics program on a computer.

RTOSs can be event-driven or time-sharing. An event-driven RTOS will switch between operations or tasks based on preassigned priorities. A time-sharing RTOS will switch between operations or tasks based on clock interrupts or specific time intervals. An RTOS

is often implemented when scheduling or timing is the most critical part of the task to be performed.

A security concern using RTOSs is that these systems are often focused and singlepurpose, leaving little room for security. They often use custom or proprietary code, which may include unknown bugs or flaws that could be discovered by attackers. An RTOS might be overloaded or distracted with bogus datasets or process requests by malware. When deploying or using RTOSs, use isolation and communication monitoring to minimize abuses.

Internet of Things

Smart devices are a range of devices that offer the user a plethora of customization options, typically through installing apps, and may take advantage of on-device or in-the-cloud machine learning (ML) processing. The products that can be labeled “smart devices” are constantly expanding and already include smartphones, tablets, music players, home assistants, extreme sport cameras, virtual reality/augmented reality (VR/AR) systems, and fitness trackers.

The Internet of Things (IoT) is a class of smart devices that are internet-connected in order to provide automation, remote control, or AI processing to appliances or devices. IoT

may often perform functions and operate similar to an embedded system, but they are different. An IoT device is almost always a separate and distinct hardware device that is used on its own or in conjunction with an existing system (such as a smart IoT thermostat for a heating, ventilation, and air-conditioning [HVAC] system). An embedded system is one where the computer control component has been integrated into the structure, design, and operation of the larger mechanism, often even built into the same chassis or case.

The security issues related to IoT are often about access and encryption. All too often an IoT device was not designed with security as a core concept or even an afterthought. This has resulted in numerous home and office network security breaches. Additionally, once an attacker has remote access to or through an IoT device, they may be able to access other devices on the compromised network. When electing to install IoT equipment, evaluate the security of the device as well as the security reputation of the vendor. If the device does not have the ability to meet or accept your existing security baseline, then don’t compromise your security just for a flashy gadget.

One possible secure implementation is to deploy a distinct network for the IoT equipment, which is kept separate and isolated from the primary network. This configuration is

often known as three dumb routers (see www.grc.com/sn/sn-545.pdf or www.pcper

.com/reviews/General-Tech/Steve-Gibsons-Three-Router-Solution-IOT- Insecurity). Other standard security practices are beneficial to IoT, including keeping systems patched, limiting physical and logical access, monitoring all activity, and implementing firewalls and filtering.

Wearable technology or wearables are offshoots of smart devices and IoT devices that are specifically designed to be worn by an individual. The most common examples of wearable technology are smart watches and fitness trackers. There are an astounding number of available options, with a wide range of features and security capabilities. When selecting

a wearable device, consider the security implications. Is the data being collected in a cloud service that is secured for private use or is it made publicly available? What alternative uses is the collected data going to be used for? Is the communication between the device and the collection

service encrypted? And can you delete your data and profile from the service completely if you stop using the device?

Although we often associate smart devices and IoT with home or personal use, they are also a concern to every organization. This is partly because of the use of mobile devices by employees within the company’s facilities and even on the organizational network.

Another concern is that many IoT or networked automation devices are often used in the business environment. This includes environmental controls, such as HVAC management, air quality control, debris and smoke detection, lighting controls, door automation, personnel and asset tracking, and consumable inventory management and auto-reordering (such as coffee, snacks, printer toner, paper, and other office supplies). Thus, both smart devices and IoT devices are potential elements of a modern business network that need appropriate security management and oversight. For some additional reading on the importance of proper security management of smart devices and IoT equipment, see “NIST Initiatives in IoT” at www.nist.gov/itl/applied-cybersecurity/nist-initiatives-iot.

A common IoT device deployed in a business environment is sensors. Sensors can measure just about anything, including temperature, humidity, light levels, dust particles, movement, acceleration, and air/liquid flow. Sensors can be linked with cyber-physical systems to automatically adjust or alter operations based on the sensor’s measurements, such as turning on the air conditioning when the temperature rises above a threshold. Sensors can also be linked to ICS, DCS, and SCADA solutions.

The precautions related to facility automation devices are the same as for smart devices, IoT, and wearables. Always consider the security implications, evaluate the included or lacking security features, consider implementing the devices in an isolated network away from your other computer equipment, and only use solutions that provide robust authentication and encryption.

Often IoT devices—in fact, almost all hardware and software—will have insecure or weak defaults. Never assume defaults are good enough. Always evaluate the setting and configuration options of acquired IoT products and make changes that optimize security and support business functions. This is especially relevant to default passwords, which must always be changed and verified.

Industrial Internet of Things (IIoT) is a derivative of IoT that focuses more on industrial, engineering, manufacturing, or infrastructure level oversight, automation, management, and sensing. IIoT is an evolution of ICS and DCS that integrates cloud services to perform data collection, analysis, optimization, and automation. Examples of IIoT include edge computing and fog computing (see the section “Edge and Fog Computing,” earlier in this chapter).

Edge and Fog Computing

Edge computing is a philosophy of network design where data and the compute resources are located as close as possible in order to optimize bandwidth use while minimizing latency. In edge computing, the intelligence and processing are contained within each device. Thus, rather than having to send data off to a master processing entity, each device can process its own data locally. The architecture of edge computing performs computations closer to the data source, which is at or near the edge of the network. This is distinct from performing processing in the cloud on data transmitted from remote locations. Edge computing is often implemented as an element of IIoT (Industrial Internet of Things) solutions, but edge computing is not limited to this type of implementation.

Edge computing can be viewed as the next evolution of computing concepts. Originally, computing was accomplished on core mainframe computers where applications were executed on the central system but where controlled or manipulated via thin clients. Then the distributed concept of client/server moved computing out to endpoint devices. This allowed for the execution of decentralized applications (i.e., not centrally controlled) that ran locally on the endpoint system. From there, virtualization led to cloud computing. Cloud computing is a type of centralized application execution on remote data center systems, controlled remotely by endpoints. Finally, edge computing is the use of devices that are close to or at

the endpoint where applications are centrally controlled but the actual execution is as close to the user or network edge as possible.

One potential use for edge devices is the deployment of mini-web servers by ISPs to host static or simple pages for popular sites that are located nearer to the bulk of common visitors than the main web servers. This speeds up the initial access to the front page of a popular organization’s web presence, but then subsequent page visits are directed to and served by core or primary web servers that may be located elsewhere. Other examples of edge computing solution include security systems, motion detecting cameras, image recognition systems, IoT and IIoT devices, self-driving cars, optimized content delivery network (CDN) caching, medical monitoring devices, and video conferencing solutions.

Fog computing is another example of advanced computation architectures, which is also often used as an element in an IIoT deployment. Fog computing relies on sensors, IoT

devices, or even edge computing devices to collect data, and then transfer it back to a central location for processing. The fog computing processing location is positioned in the LAN. Thus, with fog computing, intelligence and processing are centralized in the LAN. The centralized compute power processes information gathered from the fog of disparate devices and sensors.

In short, edge computing performs processing on the distributed edge systems, whereas fog computing performs centralized processing of the data collected by the distributed sensors. Both edge and fog computing can often take advantage of or integrate the use of microcontrollers, embedded devices, static devices, cyber-physical systems, and IoT equipment.

Embedded Devices and Cyber-Physical

Systems

An embedded system is any form of computing component added to an existing mechanical or electrical system for the purpose of providing automation, remote control, and/or monitoring. The embedded system is typically designed around a limited set of specific functions in relation to the larger product to which it is attached. It may consist of the same components found in a typical computer system, or it may be a microcontroller (an integrated chip with onboard memory and peripheral ports).

Microcontrollers

A microcontroller is similar to, but less complex than a system on a chip, or SoC (see Chapter 11). A microcontroller may be a component of an SoC. A microcontroller is a small computer consisting of a CPU (with one or more cores), memory, various input/ output capabilities, RAM, and often nonvolatile storage in the form of flash or ROM/ PROM/EEPROM. Examples include Raspberry Pi, Arduino, and a field-programmable gate array (FPGA).